The use of surrogate imaging biomarkers as primary measures of disease state and progression has gained favor over the past decade. Nuclear magnetic resonance spectroscopy (NMRS) and magnetic resonance imaging (MRI) are formidable non-invasive tools for quantitatively interrogating materials. This can be attributed to the fact that MR measurements can be sensitized to a number of sample properties. A set of magnetic characteristics may well be unique to a one type of nucleus, chemical structure, chemical compound, material, or dynamic process in a sample. When present, the magnetic properties of a sample will be altered and MR experimental protocol may be designed such that measurements will be sensitive to the change.
The ability to ascertain how factors like those listed above alter the magnetic properties of a sample quantitatively could provide a wealth of information useful for determining the composition and condition of a sample. Where MRI methods are employed, these quantitative measures could be correlated with spatial locations within the sample to yield information about the internal organization of differentiated materials. In conjunction with its non-destructive nature, these properties make NMRS and MRI excellent choices for mining information about the static and dynamic properties of living biological systems. Developing the ability to extract quantitative information about living tissue using NMRS and MRI methods could help researchers and clinicians identify subtle changes in tissue properties with greater sensitivity and specificity. It follows that such methods may be used to identify and map surrogate biomarkers for use in research, diagnosis, and monitoring of disease progression as well as offer a safe means of evaluating drug efficacy.
The field of MRI concerned with generating quantitative maps of sample properties is known as quantitative MRI (QMRI). The use of QMRI in research and clinical practice constitutes a significant paradigm shift from the qualitative methods used to interpret property weighted images. Qualitative assessment methods are employed where images are sensitized or “weighted” to a particular property, e.g. T1, T2, or diffusion. Within the resulting image, relative intensity may differ from area to area. While weighting implies that contrast is thought to be primarily due to a certain property, it is accepted that other properties influence the intensities in the resulting image. By definition, attempts are not made to quantitatively determine contributions from other properties that are likely present. In QMRI, the objective is to correlate the quantified or measured value of a property of interest with a spatial location in a sample. This can be done in order to glean a better understanding of the chemical, structural, or dynamic properties of the sample. It could also identify improved imaging biomarkers thus enhancing the ability to extract information about the condition of a biological sample.
When using MRI to generate images for qualitative evaluation, the multiplicity of magnetic properties to which the image can be sensitized to is often considered one of the strengths of the modality. However, quantitatively separating the contributions to the measured MR signal, used for image reconstruction, from each influence is extremely challenging. Attempting to accurately measure or reproducibly quantify a property using MR methods is a complicated endeavor.
A number of MR studies have been conducted wherein with the careful quantification of an MR parameter in mind. Historically the methods used in such studies have required long scan times for data collection, making them unsuitable for clinical use. Recently, two promising QMRI methods have been reported. In multicomponent driven equilibrium single pulse observation of T1/T2 (mcDESPOT), imaging data is collected over the course of several steady state MR experiments. A multicompartment model of biological tissue is then implemented using a matrix formalism in order to analyze the results. This method has been employed to study neurodegenerative diseases as well as brain development. The scan times of roughly 30 minutes have been reported in these studies. It has been suggested that, given the complexity of the biological tissue model used for analysis and signal to noise in the steady state measurements, longer scan times would be required to improve quantitative confidence in the resulting parameters values. Additionally, it has been known for some time that measurements made using periodic and steady state sequences are not strictly periodic. More recently a method which employs an aperiodic sequence of excitation pulses and measurement sensitizing strategies has been described. Magnetic resonance fingerprinting (MRF) has been used to generate multiple parametric maps from data collected over the course of an imaging experiment that required only 12 seconds of scan time. The short scan times required for imaging may make the method extremely attractive to researchers and clinicians alike. However, because of the aperiodic nature of the MR sequence, measurements cannot be assumed to be equally weighted. Each measurement is comprised of a full, under sampled, imaging data set to be used for reconstruction. MRF is a relatively new method and the full implications of collecting data in this manner are not well understood.
The present invention develops a novel QMRI method which may produce repeatable MR data wherein the measurements may be assumed to be equally weighted. This allows for the rapid collection of a large amount of MR data which may be well suited for quantitative analysis. The present invention has surprising results of showing that, starting from a state of near zero bulk magnetization, as contrasted with starting from a presumed equilibrium configuration, may lead to more repeatable outcomes, allowing statistical strengthening of results by combining repeated measurements. And reaching states of near zero magnetization from arbitrary post-measurement states may be achieved very quickly by means of nulling sequences.
This result is surprising because the prior art has mostly striven to allow sufficient time for the specimen to relax toward the equilibrium configuration between repeated measurements, which considerably lengthens the processes of collecting an ensemble of measurements. And this has not been shown to provide consistently repeatable results of good statistical quality. Relaxation toward equilibrium configuration occurs asymptotically with exponential approach, whose time constant is largely determined by physical characteristics of the specimen. Relaxation times with e-folding periods ranging from 2000 ms to 4000 ms are commonplace where cerebrospinal fluid and water are primary constituents of the specimen. There has been considerable documented variation in how close to steady state equilibrium the starting conditions of repeated measurements may have been, which can only be overcome by waiting undesirably long times between measurements.